Enhancing Privacy While Preserving Context in Text Transformations by Large Language Models
Data security is a critical concern for Internet users, primarily as more people rely on social networks and online tools daily. Despite the convenience, many users are unaware of the risks posed to their sensitive and personal data. This study addresses this issue by presenting a comprehensive solu...
Saved in:
Main Authors: | Tymon Lesław Żarski, Artur Janicki |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/16/1/49 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Using the PubAnnotation ecosystem to perform agile text mining on : a tutorial review
by: Hee-Jo Nam, et al.
Published: (2020-06-01) -
Improving spaCy dependency annotation and PoS tagging web service using independent NER services
by: Nico Colic, et al.
Published: (2019-06-01) -
A comprehensive dataset and neural network approach for named entity recognition in the Uzbek languageMendeley Data
by: Davlatyor Mengliev, et al.
Published: (2025-02-01) -
Instruction and demonstration-based secure service attribute generation mechanism for textual data
by: LI Chenhao, et al.
Published: (2024-12-01) -
Metamorphic testing of named entity recognition systems: A case study
by: Yezi Xu, et al.
Published: (2022-08-01)